CFD ANALYSIS OF FIRST STAGE NOZZLE COOLING OPTIMIZATION IN POWER STATION GAS TURBINE

2015 ◽  
Vol 76 (5) ◽  
Author(s):  
Hasril Hasini ◽  
Siti Sarah Ain Fadhil ◽  
Mohd Nasharuddin Mohd Jaafar ◽  
Norhazwani Abdul Malek ◽  
Mohd. Haffis Ujir
Keyword(s):  
Gas Turbine ◽  
Transfer Problem ◽  
Maximum Yield ◽  
Safety Margin ◽  
Power Station ◽  
Case Scenario ◽  
Preliminary Calculation ◽  
Worst Case ◽  
Cloud Data ◽  
Computational Fluid Dynamics Analysis

Computational Fluid Dynamics analysis on First Stage Nozzle in full scale multi-stage power station gas turbine has been carried out. The main aim is to investigate the turbine thermal performance when cooling rate decreases at certain level. All calculations were executed using commercial CFD code, ANSYS FLUENT which is able to accurately predict the flow and conjugate heat transfer problem as demonstrated in this investigation. The modelling of gas turbine nozzle is assisted by geometric cloud data obtained from 3D scan. Preliminary calculation shows that at the given worst case scenario for, the maximum thermal stress experienced by the component is within the maximum yield strength of the nozzle material. However, the safety margin between the predicted stress and maximum allowable stress is very small. 

Customer Adapted Maintenance Plan (CAMP): A Process for Optimization of Gas Turbine Maintenance

2008 ◽  
Author(s):  
Mathias Wa¨rja ◽  
Pontus Slottner ◽  
Markus Bohlin
Keyword(s):  
Gas Turbine ◽  
Preventive Maintenance ◽  
Gas Turbines ◽  
Measurement Techniques ◽  
Test Methods ◽  
Detailed Knowledge ◽  
Critical Systems ◽  
Case Scenario ◽  
Worst Case ◽  
Maintenance Plan

Maintaining high levels of availability and reliability are essential objectives for many industries, especially those that are subject to high costs due to shutdowns of critical systems, e.g. gas turbines. To utilize these systems as effectively as possible, preventive maintenance must be optimized. Determining what is optimal is, however, a multi-variable task requiring detailed knowledge about the components in the system and their different damage mechanisms. These factors have always affected the condition of the gas turbine and maintenance actions, but only recently has it been possible to estimate and measure them correctly for individual components during operation. In the past, it was necessary to construct maintenance intervals from the most critical component (or components), requiring the highest maintenance frequency. An additional worst-case scenario margin was also necessary, taking into account factors such as possible load variation, differences in environment (affecting e.g. power turbine temperatures) and other sources of uncertainty. These uncertainties together have determined traditional maintenance planning, with maintenance packages each containing a set of maintenance activities for a set of components being predetermined and preplanned. With the new CAMP approach, the maintenance strategy is to reach a Retirement For Cause (RFC) strategy, where components are not replaced until a potential failure has been detected. This requires measurement techniques that can monitor how the gas turbine is operated, prognostics capabilities that foresee maintenance needs, and test methods that can determine the state of a component during maintenance events. One important part of CAMP is therefore a prognostic tool which tells us the condition, and therefore the maintenance needs, of individual components within the gas turbine. To handle this information and efficiently make a preventive maintenance plan, software for gas turbine maintenance optimization has been developed. The software can not only calculate the most efficient point in time for a maintenance action, it can also adjust the maintenance plan to any customer’s specific demands. This paper describes the model, gathering and processing of information, risk assessment performance and the result from an optimization which groups maintenance actions as a result of customer prioritized demands. It also describes the software layout and how it is used.

Linear Growth Rate Estimation From Dynamics and Statistics of Acoustic Signal Envelope in Turbulent Combustors

2016 ◽  
Vol 139 (4) ◽  
Author(s):  
Nicolas Noiray
Keyword(s):  
Gas Turbine ◽  
Acoustic Signal ◽  
Growth Rates ◽  
Linear Growth ◽  
Dynamic Pressure ◽  
Linear Growth Rate ◽  
Case Scenario ◽  
Major Step ◽  
Worst Case ◽  
Signal Envelope

Considerable research and development efforts are required to meet the targets of future gas turbine technologies in terms of performance, emissions, and operational flexibility. One of the recurring problems is the constructive coupling between flames and combustor's acoustics. These thermoacoustic interactions can cause high-amplitude dynamic pressure limit cycles, which reduce the lifetime of the hot gas path parts or in the worst-case scenario destroy these mechanical components as a result of a sudden catastrophic event. It is shown in this paper that the dynamics and the statistics of the acoustic signal envelope can be used to identify the linear growth rates hidden behind the observed pulsations, and the results are validated against numerical simulations. This is a major step forward and it will contribute to the development of future gas turbine combustors, because the knowledge of these linear growth rates is essential to develop robust active and passive systems to control these combustion instabilities.

Linear Growth Rate Estimation From Dynamics and Statistics of Acoustic Signal Envelope in Turbulent Combustors

2016 ◽  
Author(s):  
Nicolas Noiray
Keyword(s):  
Gas Turbine ◽  
Acoustic Signal ◽  
Growth Rates ◽  
Linear Growth ◽  
Dynamic Pressure ◽  
Linear Growth Rate ◽  
Case Scenario ◽  
Major Step ◽  
Worst Case ◽  
Signal Envelope

Considerable research and development efforts are required to meet the targets of future gas turbine technologies in terms of performance, emissions and operational flexibility. One of the recurring problem is the constructive coupling between flames and combustor’s acoustics. These thermoacoustic interactions can cause high amplitude dynamic pressure limit cycles, which reduce the lifetime of the hot-gas-path parts or in the worst case scenario destroy these mechanical components as a result of a sudden catastrophic event. It is shown in this paper that the dynamics and the statistics of the acoustic signal envelope can be used to identify the linear growth rates hidden behind the observed pulsations, and the results are validated against numerical simulations. This is a major step forward and it will contribute to the development of future gas turbine combustors, because the knowledge of these linear growth rates is essential to develop robust active and passive systems to control these combustion instabilities.

Reducing Probabilistic Weather Forecasts to the Worst Case Scenario: Anchoring Effects

2008 ◽  
Author(s):  
Sonia Savelli ◽  
Susan Joslyn ◽  
Limor Nadav-Greenberg ◽  
Queena Chen
Keyword(s):  
Case Scenario ◽  
Worst Case ◽  
Weather Forecasts ◽  
Worst Case Scenario ◽  
Anchoring Effects

EXPEDITION TO MALI, 2020

2020 ◽  
pp. 12-28
Author(s):  
D. V. Vaniukova ◽  
◽  
P. A. Kutsenkov ◽  
Keyword(s):  
Mass Murder ◽  
The State ◽  
Case Scenario ◽  
Worst Case ◽  
Traditional Art ◽  
Peter The Great ◽  
State Museum ◽  
Bobo Dioulasso ◽  
Oriental Studies ◽  
The Village

The research expedition of the Institute of Oriental studies of the Russian Academy of Sciences has been working in Mali since 2015. Since 2017, it has been attended by employees of the State Museum of the East. The task of the expedition is to study the transformation of traditional Dogon culture in the context of globalization, as well as to collect ethnographic information (life, customs, features of the traditional social and political structure); to collect oral historical legends; to study the history, existence, and transformation of artistic tradition in the villages of the Dogon Country in modern conditions; collecting items of Ethnography and art to add to the collection of the African collection of the. Peter the Great Museum (Kunstkamera, Saint Petersburg) and the State Museum of Oriental Arts (Moscow). The plan of the expedition in January 2020 included additional items, namely, the study of the functioning of the antique market in Mali (the “path” of things from villages to cities, which is important for attributing works of traditional art). The geography of our research was significantly expanded to the regions of Sikasso and Koulikoro in Mali, as well as to the city of Bobo-Dioulasso and its surroundings in Burkina Faso, which is related to the study of migrations to the Bandiagara Highlands. In addition, the plan of the expedition included organization of a photo exhibition in the Museum of the village of Endé and some educational projects. Unfortunately, after the mass murder in March 2019 in the village of Ogossogou-Pel, where more than one hundred and seventy people were killed, events in the Dogon Country began to develop in the worst-case scenario: The incessant provocations after that revived the old feud between the Pel (Fulbe) pastoralists and the Dogon farmers. So far, this hostility and mutual distrust has not yet developed into a full-scale ethnic conflict, but, unfortunately, such a development now seems quite likely.

Risk-Based Robust Bidding Strategies for EVs’ Aggregators in Day-ahead Markets with Uncertainty

2020 ◽  
Author(s):  
Ahmed Abdelmoaty ◽  
Wessam Mesbah ◽  
Mohammad A. M. Abdel-Aal ◽  
Ali T. Alawami
Keyword(s):  
Robust Optimization ◽  
Electricity Market ◽  
Real Life ◽  
Optimization Approach ◽  
Case Scenario ◽  
Worst Case ◽  
Bidding Strategies ◽  
Wind Generators ◽  
Proposed Model ◽  
Optimal Bidding

In the recent electricity market framework, the profit of the generation companies depends on the decision of the operator on the schedule of its units, the energy price, and the optimal bidding strategies. Due to the expanded integration of uncertain renewable generators which is highly intermittent such as wind plants, the coordination with other facilities to mitigate the risks of imbalances is mandatory. Accordingly, coordination of wind generators with the evolutionary Electric Vehicles (EVs) is expected to boost the performance of the grid. In this paper, we propose a robust optimization approach for the coordination between the wind-thermal generators and the EVs in a virtual<br>power plant (VPP) environment. The objective of maximizing the profit of the VPP Operator (VPPO) is studied. The optimal bidding strategy of the VPPO in the day-ahead market under uncertainties of wind power, energy<br>prices, imbalance prices, and demand is obtained for the worst case scenario. A case study is conducted to assess the e?effectiveness of the proposed model in terms of the VPPO's profit. A comparison between the proposed model and the scenario-based optimization was introduced. Our results confirmed that, although the conservative behavior of the worst-case robust optimization model, it helps the decision maker from the fluctuations of the uncertain parameters involved in the production and bidding processes. In addition, robust optimization is a more tractable problem and does not suffer from<br>the high computation burden associated with scenario-based stochastic programming. This makes it more practical for real-life scenarios.<br>

scholarly journals A Thermally Conductive Pt/AAO Catalyst for Hydrogen Passive Autocatalytic Recombination

Catalysts ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 491
Author(s):  
Alina E. Kozhukhova ◽  
Stephanus P. du Preez ◽  
Aleksander A. Malakhov ◽  
Dmitri G. Bessarabov
Keyword(s):  
Electron Microscopy ◽  
Particle Size ◽  
Combustion Temperature ◽  
Volume Fraction ◽  
Morphological Characteristics ◽  
Al Alloy ◽  
Impregnation Method ◽  
Case Scenario ◽  
Worst Case ◽  
Thermal Distribution

In this study, a Pt/anodized aluminum oxide (AAO) catalyst was prepared by the anodization of an Al alloy (Al6082, 97.5% Al), followed by the incorporation of Pt via an incipient wet impregnation method. Then, the Pt/AAO catalyst was evaluated for autocatalytic hydrogen recombination. The Pt/AAO catalyst’s morphological characteristics were determined by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The average Pt particle size was determined to be 3.0 ± 0.6 nm. This Pt/AAO catalyst was tested for the combustion of lean hydrogen (0.5–4 vol% H2 in the air) in a recombiner section testing station. The thermal distribution throughout the catalytic surface was investigated at 3 vol% hydrogen (H2) using an infrared camera. The Al/AAO system had a high thermal conductivity, which prevents the formation of hotspots (areas where localized surface temperature is higher than an average temperature across the entire catalyst surface). In turn, the Pt stability was enhanced during catalytic hydrogen combustion (CHC). A temperature gradient over 70 mm of the Pt/AAO catalyst was 23 °C and 42 °C for catalysts with uniform and nonuniform (worst-case scenario) Pt distributions. The commercial computational fluid dynamics (CFD) code STAR-CCM+ was used to compare the experimentally observed and numerically simulated thermal distribution of the Pt/AAO catalyst. The effect of the initial H2 volume fraction on the combustion temperature and conversion of H2 was investigated. The activation energy for CHC on the Pt/AAO catalyst was 19.2 kJ/mol. Prolonged CHC was performed to assess the durability (reactive metal stability and catalytic activity) of the Pt/AAO catalyst. A stable combustion temperature of 162.8 ± 8.0 °C was maintained over 530 h of CHC. To confirm that Pt aggregation was avoided, the Pt particle size and distribution were determined by TEM before and after prolonged CHC.

scholarly journals A Comparison of Match Demands Using Ball-in-Play versus Whole Match Data in Professional Soccer Players of the English Championship

Sports ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 76
Author(s):  
Dylan Mernagh ◽  
Anthony Weldon ◽  
Josh Wass ◽  
John Phillips ◽  
Nimai Parmar ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Soccer Players ◽  
Training Methods ◽  
Case Scenario ◽  
Worst Case ◽  
Repeated Measures Design ◽  
Worst Case Scenario ◽  
Professional Soccer ◽  
Peak Match ◽  
Playing Time

This is the first study to report the whole match, ball-in-play (BiP), ball-out-of-play (BoP), and Max BiP (worst case scenario phases of play) demands of professional soccer players competing in the English Championship. Effective playing time per soccer game is typically <60 min. When the ball is out of play, players spend time repositioning themselves, which is likely less physically demanding. Consequently, reporting whole match demands may under-report the physical requirements of soccer players. Twenty professional soccer players, categorized by position (defenders, midfielders, and forwards), participated in this study. A repeated measures design was used to collect Global Positioning System (GPS) data over eight professional soccer matches in the English Championship. Data were divided into whole match and BiP data, and BiP data were further sub-divided into different time points (30–60 s, 60–90 s, and >90 s), providing peak match demands. Whole match demands recorded were compared to BiP and Max BiP, with BiP data excluding all match stoppages, providing a more precise analysis of match demands. Whole match metrics were significantly lower than BiP metrics (p < 0.05), and Max BiP for 30–60 s was significantly higher than periods between 60–90 s and >90 s. No significant differences were found between positions. BiP analysis allows for a more accurate representation of the game and physical demands imposed on professional soccer players. Through having a clearer understanding of maximum game demands in professional soccer, practitioners can design more specific training methods to better prepare players for worst case scenario passages of play.

scholarly journals Trissolcus japonicus (Hymenoptera: Scelionidae) Causes Low Levels of Parasitism in Three North American Pentatomids Under Field Conditions

2019 ◽  
Vol 19 (4) ◽  
Author(s):  
Joshua M Milnes ◽  
Elizabeth H Beers
Keyword(s):  
North American ◽  
Native Species ◽  
Classical Biological Control ◽  
The United States ◽  
Host Finding ◽  
Pest Species ◽  
Case Scenario ◽  
Worst Case ◽  
Egg Masses ◽  
Trissolcus Japonicus

Abstract Trissolcus japonicus (Ashmead), an Asian parasitoid of Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), was first detected in North America in 2014. Although testing in quarantine facilities as a candidate for classical biological control is ongoing, adventive populations have appeared in multiple sites in the United States, Canada, and Europe. Extensive laboratory testing of T. japonicus against other North American pentatomids and H. halys has revealed a higher rate of parasitism of H. halys, but not complete host specificity. However, laboratory tests are necessarily artificial, in which many host finding and acceptance cues may be circumvented. We offered sentinel egg masses of three native pentatomid (Hemiptera: Pentatomidae) pest species (Chinavia hilaris (Say), Euschistus conspersus Uhler, and Chlorochroa ligata (Say)) in a field paired-host assay in an area with a well-established adventive population of T. japonicus near Vancouver, WA. Overall, 67% of the H. halys egg masses were parasitized by T. japonicus during the 2-yr study. Despite the ‘worst case’ scenario for a field test (close proximity of the paired egg masses), the rate of parasitism (% eggs producing adult wasps) on all three native species was significantly less (0.4–8%) than that on H. halys eggs (77%). The levels of successful parasitism of T. japonicus of the three species are C. hilaris > E. conspersus > C. ligata. The potential impact of T. japonicus on these pentatomids is probably minimal.

scholarly journals Coupling Computational Fluid Dynamics Simulations and Statistical Moments for Designing Healthy Indoor Spaces

2019 ◽  
Vol 16 (5) ◽  
pp. 800 ◽  
Author(s):  
Shamia Hoque ◽  
Firoza Omar
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Air Flow ◽  
Particle Dispersion ◽  
Statistical Moments ◽  
Dispersion Pattern ◽  
Case Scenario ◽  
Worst Case ◽  
Site Specific ◽  
Indoor Spaces

Cross-contamination between occupants in an indoor space may occur due to transfer of infectious aerosols. Computational fluid dynamics (CFD) provides detailed insight into particle transport in indoor spaces. However, such simulations are site-specific. This study couples CFD with statistical moments and establishes a framework that transitions site-specific results to generating guidelines for designing “healthy” indoor spaces. Eighteen cases were simulated, and three parameters were assessed: inlet/outlet location, air changes per hour, and the presence/absence of desks. Aerosol release due to a simulated “sneeze” in a two-dimensional ventilated space was applied as a test case. Mean, standard deviation, and skewness of the velocity profiles and particle locations gave an overall picture of the spread and movement of the air flow in the domain. A parameter or configuration did not dominate the values, confirming the significance of considering the combined influence of multiple parameters for determining localized air-flow characteristics. Particle clustering occurred more when the inlet was positioned above the outlet. The particle dispersion pattern could be classified into two time zones: “near time”, <60 s, and “far time”, >120 s. Based on dosage, the 18 cases were classified into three groups ranging from worst case scenario to best case scenario.

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